基于区域梯度式学习情景的长江经济带环境治理研究

长江经济带作为国家重大战略,面临开发与保护的巨大挑战,构建科学、高效的生态环境保护机制为其保驾护航成为重中之重。作为一个流域式生态共同体,区域统筹协调下的生态环境保护和治理是根本关键。本研究导入区域协同治理理念,提出构建梯度式渐进学习环境协同治理框架,并采用数据进行长江经济带环境污染治理的多情景测度与评价实证检验了梯度间以及梯度内部的环境保护与污染治理协调机制的潜在影响。最终,从中央、区域和地方三个层面提出梯度式学习视野下长江经济带环境治理策略。

Research on Environmental Governance of the Yangtze River Economic Belt Based on Regional Gradient Learning Scenarios

The Yangtze River Economic Belt, as an important part of a major national strategy, faces great challenges in development and protection. It has become a top priority to construct a scientific and efficient ecological and environmental protection mechanism. As a basin-type ecological community, the ecological environment protection and governance under the regional coordination and coordination is the fundamental key. Research into the concept of regional collaborative management, put forward the construction of a gradient-type gradual learning environment collaborative governance framework, and use data to carry out multiple scenarios measurement and evaluation of environmental pollution control in the Yangtze River Economic Belt, and empirically test the potential impact of the environmental protection and pollution control coordination mechanisms within and between gradients. Finally, from the perspective of a gradient-based learning perspective, the Yangtze River Economic Belt environmental governance strategy was proposed from the central, regional, and local levels.